Over the past few decades, magnetic materials with various shapes and sizes have demonstrated wide potential applications, for examples, in data storage [Wang 2008, Terris 2005], magnetic sensors [Li 2003, Guo 2007, Guo 2008], biomedical [Lee 2007, Lu 2005] (i.e., drug delivery) and pharmaceutical areas [Ban 2005, Gupta 2004], and even the environmental remediation [Zang 2010]. Polymer nanocomposites (PNCs) have been well developed in the last two decades due to the combined advantages of polymers, such as lightweight, easy processability and flexibility, and excellent physiochemical characteristics of the inorganic nanomaterials such as high mechanical strength and excellent electrical, magnetic and optical properties. Therefore, magnetic PNCs have attracted wide interest for their diverse potential applications such as energy storage devices [Kim, P. 2009], electrochromic devices [Zhu 2010], electronics [Zhu 2010 II, Zhu 2010 III], microwave absorbers [Guo 2007 II, Guo 2009], and sensors [Shimada 2007].
The major challenge lying ahead to obtain high performance PNCs comes from the serious agglomeration of the nanomaterials owing to their high surface energy and large specific surface area. Thus, a lot of efforts have been made to tailor their surface property through physical and chemical approaches [Tseng 2006, Tasis 2006, Yang 2007, Guo 2006] to improve the interfacial compatibility between the inorganic fillers and the polymermatrix. To overcome the challenges in dispersing the magnetic nanoparticles (NPs) limited by the magnetically induced agglomeration, techniques including encapsulating the magnetic core with surfactant [Kataby 1997], polymer [Boyer 2009], silica [Lu 2002], and carbon [Zhang 2010] have been reported. However, these well-dispersed NPs can only be limitedly applied in specific polymers with versatile surface functionalities. Right now, most of the current research work on fabricating PNCs starts from the as-prepared NPs and polymers (or monomer) with a direct blending [Zhu 2010 III] or surface initiated polymerization method [Gun 2007 III]. A general method is of great interest to simplify the procedures while maintaining the well dispersed magnetic NPs.
The critical concentration of the fillers within the polymer matrix, where the performance of the PNCs experiences a sharp change, is often called “percolation threshold.” Almost all the physical properties, including viscoelastic, thermal, mechanical and electrical properties are related to the percolation phenomenon. Thus, various methods have been developed to determine the percolation value. Most of the current research efforts concentrate on the carbon based nanomaterials such as carbon nanotubes (CNTs) [Potschke 2002], carbon nanofibers [Zhu 2010 II, Zhu 2010 IV], carbon NPs [Kotsilkova 2005], and graphene [Kim, H. 2009] to enhance the thermal, electrical and mechanical properties of the polymers. Nanoclays [Sun 2009, Hyun 2001] are often used to improve the fire retardant performance. Potschke et al. [Potschke 2004] studied the rheological and dielectric percolation of the multiwalled CNTs/polycarbonate PNCs and found that the rheological percolation (0.5-5 wt %) is strongly dependent on the temperature and the electrical percolation is at about 1 wt %. Sandler et al. [Sandler 2003] reported a ultra low electrical percolation in the CNTs/epoxy PNCs at a loading of 0.0025 wt %. It is well-known that the percolation threshold is also dependent on the filler morphology, spherical particles are relatively difficult to reach percolation as compared to those with larger aspect ratio (like fibers and tubes). Therefore, a relatively higher loading of around 16 vol % from geometrical model [Kirkpatrick 1973, Zallen 1983] was required to reach percolation. Recently, Zhu et al. reported a low electrical percolation at 1.5 vol % with spherical Fe(core)-FeO(shell) structured NPs in epoxy resin using a surface wetting method. [Zhu 2010 111].